Using this book

0.1 Why should you read this book?

The goal of this bookdown is to provide a complete overview of the theory and methodology of two topics (at this point) within spatial capture-recapture:

  1. Integrating telemtry data to estimate resource selection functions.
  2. Optimizing sampling design toward statistical objectives

More broadly, by providing them with a thorough discussion of these advanced topics, we aim to empower our users to apply these tools in their own research.

0.2 Why should you use oSCR

The main function in oSCR performs likelihood analysis of several classes of spatial capture-recapture (SCR) models. There are also a suite of helper functions for formatting and processing data objects. Here are a few of the things that motivated our development of the package:

  1. 100% native R code, making it (reasonably) accessible to people who know R and presumably extensible by ordinary R programmers.
  2. Because it’s written in R, you can look at the code to figure out exactly what’s going on.
  3. It’s a bit slower compared to secr, but we think it’s quite robust to massive-sized problems.
  4. The data structure is relatively simple, just as ordinary R lists (for the most part).
  5. The models accommodate least-cost path models and models that include telemetry data and resource selection functions.
  6. oSCR forces you to define the state-space of the point process which we think is important to understanding an analysis.

0.3 Getting set up

So, using this book of course requires that the oSCR package is loaded:

#remotes::install_github("jaroyle/oSCR") 
library(oSCR)

But you will also need a few others:

library(ggplot2)
library(raster)
library(sf)
library(viridis)

If you have any issues or questions, we have a very responsive, and friendly user group.